About the job :

Dodge Construction Network (Dodge) is looking for a seasoned, hands-on search specialist with systems design and architecture exposure to work in our highly technical and intense development team.

This is a full-time position and reports directly to the VP, Data Architecture.

Preferred Location : Qualified candidates should be based in or near Kochi and able to work from our Kochi office as part of a hybrid schedule.

Essential Functions :

Search Platform Engineering :

- Design, build, and maintain scalable search infrastructure using Apache Solr and/or OpenSearch, including schema design, indexing pipelines, and query parsing

- Optimize search relevance through tokenization strategies, stemming, custom analyzers, boosting rules, and query-time vs. index-time tuning

- Manage and maintain search cluster configuration, replication, and high-availability operations in production environments

- Diagnose and resolve search performance issues, including slow queries, indexing bottlenecks, and relevance degradation

- Evaluate and introduce improvements to search architecture as the platform and data volumes scale

Backend Engineering :

- Develop and maintain backend services and APIs in .NET (C#), applying asynchronous patterns and dependency-injection frameworks to build reliable, scalable components

- Write Python scripts for data processing, pipeline orchestration, and ML prototype integration with the search platform

- Collaborate with data engineering teams to design and optimize data ingestion and enrichment pipelines that feed search indexes

- Ensure code quality through unit, integration, and performance testing across all components

Cloud & Infrastructure :

- Deploy and manage search workloads on AWS using ECS/EKS, Lambda, S3, IAM, and CloudFormation or CDK

- Implement and maintain CI/CD pipelines to support reliable, repeatable deployments of search services

- Apply container security best practices and contribute to infrastructure-as-code using Terraform or Pulumi where applicable

- Monitor system health, query performance, and infrastructure costs using AWS-native and third-party observability tools

AI-Assisted Development :

- Incorporate AI coding tools such as Claude Code, GitHub Copilot, or Codex into daily development workflows to accelerate delivery and code quality

- Review and validate AI-generated code for correctness, security, and alignment with team standards

- Share effective AI-assisted development practices with teammates to improve team-wide productivity and velocity

Leadership & Collaboration :

- Act as the team's subject matter expert on search technologies, providing guidance and mentorship to engineers across skill levels

- Conduct code reviews and uphold engineering standards across the team

- Translate complex search and relevance concepts into clear, accessible language for non-technical stakeholders and product partners

- Collaborate with product managers, data scientists, and other engineering teams to deliver search capabilities that power Dodge's core products

- Operate effectively in Agile/Scrum environments, contributing to sprint planning, estimation, and continuous improvement practices

Education Requirement : Bachelor's degree in a related field or equivalent education and work experience.

Required Experience, Knowledge And Skills :

- 5+ years of hands-on experience with Apache Solr and/or OpenSearch (schema design, indexing pipelines, query parsing, clustering, replication)

- 3+ years of professional .NET (C#) development, including asynchronous patterns and dependency-injection frameworks

- Python proficiency for data processing, orchestration scripts, and ML prototypes

- Proven track record deploying workloads on AWS (ECS/EKS, Lambda, S3, IAM, CloudFormation or CDK)

- Solid understanding of search relevance concepts : tokenization, stemming, analyzers, boosting, query-time vs. index-time strategies

- CI/CD and automated testing expertise (unit, integration, performance)

- Excellent communication skills; able to simplify complex technical topics for non-technical stakeholders

- Must have worked with AI-assisted development tools (Claude, Copilot, Codex, etc.)

Preferred Experience, Knowledge And Skills :

- Knowledge of search in construction or AEC industry datasets

- Experience with Infrastructure as Code (Terraform, Pulumi)

- Familiarity with container security best practices and AWS Well-Architected Framework

- Familiarity with other distributed search technologies